Radical Competency in the Age of AI
Part Two in a Series
The interesting thing about AI is not what it replaces. It is what it reveals.
I’ve been watching this play out in real time over the last year. Teams bring in automation tools and something predictable happens: the people who were already good at their jobs get better and faster. The people who were struggling? They are still struggling, just with fancier tools.
AI is not a personality transplant.
It does not turn someone unreliable into someone you can count on. It does not teach anticipation or judgment or the ability to read a situation and know what actually needs doing. What it does is remove some of the grunt work that used to occupy everyone’s time, and in doing so, it makes the gap between radical competency and everything else a lot more visible.
If you were already the person who saw problems coming and handled them quietly, AI just gave you more capacity to do that. You can automate the repetitive stuff and spend your energy on the work that actually requires a human brain; the kind of thinking that involves context, nuance, and knowing what leadership needs before they ask for it.
But if you were the person who needed three reminders to finish a task, or who turned every simple request into a production on why it can’t happen on time (if ever), or who somehow always managed to be busy without producing much?
AI does not fix that. It just makes it harder to hide.
This is not about being cruel to people who are trying. Plenty of good, competent people are going to find their roles changing because automation handles parts of what they used to do. That is real and it is not their fault. A skilled data analyst whose job was mostly pulling reports is not suddenly incompetent because software can pull those reports faster; they are just in a spot where the work is shifting under their feet, and they need to figure out what comes next.
The difference is in how people respond to that shift. The radically competent adapt. They look at what the tools can do and figure out how to use that capacity to solve bigger problems. They do not fight the change or pretend it is not happening. They lean in and find new ways to be useful.
Then there are the people who survived on organizational inertia, creating work instead of doing it, making everything take longer than it should. For them, AI is not a tool. It is exposure. Because when the busy work disappears, what is left is the question: what do you actually contribute here?
I worked with someone years ago who was a master at looking productive. Lots of emails. Lots of meetings. Lots of talk about “circling back” and “syncing up.” But if you paid attention, nothing ever actually moved forward when he touched it. He was not malicious; just not very good. And for a long time, the system absorbed that because others picked up the slack. AI would not save him, it would just make it obvious that he was not solving problems: he was one.
Compare that to the person I mentioned in the first essay in this series. The one who listened, nodded once, and came back with the solution. AI would help her clear obstacles twice as fast and still have time left over to see the next three problems coming.
The radically competent are not worried about automation.
They are energized by it. Because they have been bogged down for years doing work that should not require a human, and now they do not have to. They can focus on the stuff that actually matters. The judgment calls. The creative problem-solving. The ability to see what is not being said in a meeting and address it before it becomes a crisis.
That is not something you can automate. And it is not something you can fake.
If you are reading this and wondering where you fall, here is a test. When the repetitive parts of your job disappear, what is left? If the answer is not much, that is worth thinking about. Not because you are doomed, but because you have time to build something better.
Learn the skills that do not get automated. Get good at anticipating. Practice solving problems nobody asked you to solve yet. Become the person the boss does not have to worry about.
If the answer to When the repetitive parts of your job disappear, what is left? is a lot, then you are probably fine. Keep doing what you are doing. Stay curious. Keep adapting. Radical competency is not a fixed state. It is a habit. And the people who practice it do not stop just because the tools change.
AI is not always the villain here; it shows you who was already doing the work and who was just occupying space. That might sound harsh, but it is also clarifying. And clarity, even uncomfortable clarity, is better than pretending things are fine when they are not.
Organizations are going to get leaner. That is already happening. I’ll wager that most of the people who stay will be the ones who make things easier, not harder. The ones who solve more problems than they create.
If that is you, keep going. If it is not, you have got time to change that. But not unlimited time.
The work is changing. The question is whether you are changing with it.
About the Radical Competency Series:
Radical Competency is my ongoing exploration of the habits, mindsets, and instincts that separate people who merely get through their work from those who shape it. These essays look at context, clarity, power, leadership, pattern recognition, and the everyday skills that never appear on a job posting but determine how far someone can go. The series draws on history, psychology, liberal arts thinking, and lived experience from the world of crisis communications. It will eventually form the backbone of a larger project.
Another edition in this series is available here, with more to come. Subscribe now and never miss a post: